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System identification and linearisation using genetic algorithms with simulated annealing

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4 Author(s)

This paper develops high performance system identification and linearisation techniques, using a genetic algorithm. The algorithm is fine tuned by simulated annealing, which yields a faster convergence and a more accurate search. This global search technique is used to identify the parameters of a system described by an ARMAX model in the presence of white noise and to approximate a nonlinear multivariable system by a linear time-invariant state space model. Results obtained show that simple step input can be used for effective system identification and linearisation with much higher performance than conventional means

Published in:

Genetic Algorithms in Engineering Systems: Innovations and Applications, 1995. GALESIA. First International Conference on (Conf. Publ. No. 414)

Date of Conference:

12-14 Sep 1995